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- Type of Document: M.Sc. Thesis
- Language: Farsi
- Document No: 45659 (05)
- University: Sharif University of Technology
- Department: Electrical Engineering
- Advisor(s): Namvar, Mehrzad
- Abstract:
- Fault detection and identification is one of the major issues and challenges in the field of engineering and currently is considered as an active field of research. As the replacement of human in dangerous or inaccessible environments, robotic mechanical systems can be used which exposes to a variety of stresses and actions that causes faults in the actuators or sensors. Accordingly, detection of fault at the earliest possible time after the fault accurence and its identification such that real flaw waveform is being extracted, can prevent more damage to the system without any need to human immediate interference. Model based approach in recent decades has shown their ability to detection and identification of faults in the area of robotic systems.
Faults and failures in robotic systems commonly are found in the joints of the robot or mainly related to the output sensors. The reliability of any model based fault detection and identification depends on the level of uncertainty in the model of system. An appropriate threshold may isolate effects of the faults due to individual uncertainties. Adaptive, robust and robust adaptive algorithms proposed in this paper help to determine threshold with less conservative on the uncertainty, leading to increase of sensitivity to added faults in joint torques. Fault estimation algorithm shows suitable operation in detecting of actuator’s fault. Performance of proposed algorithm is provided using two degrees of freedom SCARA robot dynamic equation.
- Keywords:
- Robot Manipulator ; Fault Detection ; Fault Isolation ; Adaptive Method ; Robust Schemes ; Robust-Adaptive Schemes
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